A Guiding Principle for Causal Decision Problems

M. Gonzalez-Soto; L. E. Sucar; H. J. Escalante

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arXiv · 1902.02279

A Guiding Principle for Causal Decision Problems

M. Gonzalez-Soto·L. E. Sucar·H. J. Escalante

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Abstract

We define a Causal Decision Problem as a Decision Problem where the available actions, the family of uncertain events and the set of outcomes are related through the variables of a Causal Graphical Model $\mathcal{G}$. A solution criteria based on Pearl's Do-Calculus and the Expected Utility criteria for rational preferences is proposed. The implementation of this criteria leads to an on-line decision making procedure that has been shown to have similar performance to classic Reinforcement Learning algorithms while allowing for a causal model of an environment to be learned. Thus, we aim to provide the theoretical guarantees of the usefulness and optimality of a decision making procedure based on causal information.

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BibTeX RIS

M. Gonzalez-Soto, L. E. Sucar, H. J. Escalante. 2019-02-06. A Guiding Principle for Causal Decision Problems. https://arxiv.org/abs/1902.02279

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